2026-09-20T07:02:08Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1626802025-09-19T04:48:58Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Graves, Stephen
Li, Joseph
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2025-09-18T14:26:45Z
2025-09-18T14:26:45Z
2025-05
2025-06-23T14:02:50.612Z
https://hdl.handle.net/1721.1/162680
0009-0009-3760-2455
Managing inventory effectively is a consistently difficult challenge for many large online retailers. This problem is exacerbated when dealing with low-volume items, which often occupy a disproportionately large proportion of inventory space and resources. This research lays out a foundation for investigating how to optimally place inventory across fulfillment centers (FCs) and higher-echelon storage facilities (HEFs).
A simulation has been built that considers demand rates, relevant costs (handling, shipping, holding, etc.), and other relevant metrics (review period, lead time, safety factor, etc.). The model closely mimics how a particular large online retailer functions. It can generate reports showing how costs and fill rates change with tweaks to specific inputs or methods of choosing how to allocate inventory. Building on this simulation, our analysis suggests that this research could lead to significant cost savings and better customer service.
MNG
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Analyzing Inventory Placement of Low-Volume Items in Online Retail
Thesis
application/pdf
Master
Publication
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unknown
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<Abstract>Managing inventory effectively is a consistently difficult challenge for many large online retailers. This problem is exacerbated when dealing with low-volume items, which often occupy a disproportionately large proportion of inventory space and resources. This research lays out a foundation for investigating how to optimally place inventory across fulfillment centers (FCs) and higher-echelon storage facilities (HEFs).
A simulation has been built that considers demand rates, relevant costs (handling, shipping, holding, etc.), and other relevant metrics (review period, lead time, safety factor, etc.). The model closely mimics how a particular large online retailer functions. It can generate reports showing how costs and fill rates change with tweaks to specific inputs or methods of choosing how to allocate inventory. Building on this simulation, our analysis suggests that this research could lead to significant cost savings and better customer service.</Abstract>
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